code: def _corners_to_center_format_numpy(
      bboxes_corners: np.ndarray,
  ) -> np.ndarray:
      (
          top_left_x,
          top_left_y,
          bottom_right_x,
          bottom_right_y,
      ) = bboxes_corners.T
      bboxes_center = np.stack(
          [
              (top_left_x + bottom_right_x) / 2,  # center x
              (top_left_y + bottom_right_y) / 2,  # center y
              (bottom_right_x - top_left_x),  # width
              (bottom_right_y - top_left_y),  # height
          ],
          axis=-1,
      )
      return bboxes_center
  
imports: import warnings
  from typing import Iterable, List, Optional, Tuple, Union
  import numpy
  from .image_utils import ChannelDimension, ImageInput, get_channel_dimension_axis, get_image_size, infer_channel_dimension_format
  from .utils import ExplicitEnum, TensorType, is_jax_tensor, is_tf_tensor, is_torch_tensor
  from .utils.import_utils import is_flax_available, is_tf_available, is_torch_available, is_vision_available, requires_backends
label_desc: Use image node_id 14 for calling a global function with example usage: _corners_to_center_format_numpy(bboxes_corners) and returns: bboxes_center